Automatic speech recognition (ASR) systems can suffer from transcription errors. These errors can occur due to a variety of reasons, such as, garbled speech inputs, speech inputs having noisy backgrounds, or speech inputs containing words that are phonetically similar to other words. Further, in real-time ASR systems, compromises in accuracy can be implemented to achieve acceptable latency times. For example, smaller vocabulary models or less robust speech recognition engines can be implemented. These compromises can contribute to transcription errors. Conventionally, each speech input received by an ASR system can be processed identically. However, processing all speech inputs identically can result in similar transcription errors repeatedly reoccurring, which can lead to frustration on the part of the user and poor user experience.